Increased risk of recurrent stroke in patients with impaired kidney function: results of a pooled analysis of individual patient data from the MICON international collaboration
Bibliographic record
Abstract
Background Patients with chronic kidney disease are at increased risk of stroke and frequently have cerebral microbleeds. Whether such patients also encounter an increased risk of recurrent stroke has not been firmly established. We aimed to determine whether impaired kidney function is associated with the risk of recurrent stroke, and microbleed presence, distribution and severity. Methods We used pooled data from the Microbleeds International Collaborate Network to investigate associations of impaired kidney function, defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. Our primary outcome was a composite of recurrent ischaemic stroke (IS) and intracranial haemorrhage (ICrH). Secondary outcomes included: (1) individual components of the primary outcome; (2) modification of the primary outcome by microbleed presence or anticoagulant use and (3) microbleed presence, distribution and severity. Results 11 175 patients (mean age 70.7±12.6, 42% female) were included, of which 2815 (25.2%) had impaired kidney function. Compared with eGFR ≥60, eGFR <60 was associated with a higher risk of the primary outcome (adjusted HR, aHR 1.33 (95% CI 1.14 to 1.56), p<0.001) and higher rates of the recurrent IS (aHR 1.33 (95% CI 1.12 to 1.58)). Reduced eGFR was not associated with ICrH risk (aHR 1.07 (95% CI 0.70 to 1.60)). eGFR was also associated with microbleed presence (adjusted OR, aOR 1.14 (95% CI 1.03 to 1.26)) and severity (aOR 1.17 (95% CI 1.06 to 1.29)). Compared with having no microbleeds, eGFR was lower in those with strictly lobar microbleeds (adjusted mean difference (aMD) −2.10 mL/min/1.73 cm2(95% CI −3.39 to −0.81)) and mixed microbleeds (aMD −2.42 (95% CI −3.70 to −1.15)), but not strictly deep microbleeds (aMD −0.67 (95% CI −1.85 to 0.51)). Conclusions In patients with IS or transient ischaemic attack, impaired kidney function was associated with a higher risk of recurrent stroke and higher microbleeds burden, compared with those with normal kidney function. Further research is needed to investigate potential additional measures for secondary prevention in this high-risk group.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.019 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".